TY  - JOUR
AU  - Feng, Xiaoshuang
AU  - Goodley, Patrick
AU  - Alcala, Karine
AU  - Guida, Florence
AU  - Kaaks, Rudolf
AU  - Vermeulen, Roel
AU  - Downward, George S
AU  - Bonet, Catalina
AU  - Colorado-Yohar, Sandra M
AU  - Albanes, Demetrius
AU  - Weinstein, Stephanie J
AU  - Goldberg, Marcel
AU  - Zins, Marie
AU  - Relton, Caroline
AU  - Langhammer, Arnulf
AU  - Skogholt, Anne Heidi
AU  - Johansson, Mattias
AU  - Robbins, Hilary A
TI  - Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis.
JO  - The lancet / Digital health
VL  - 6
IS  - 9
SN  - 2589-7500
CY  - London
PB  - The Lancet
M1  - DKFZ-2024-01722
SP  - e614 - e624
PY  - 2024
AB  - Lung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts.We analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCOm2012), the Lung Cancer Risk Assessment Tool (LCRAT), the Lung Cancer Death Risk Assessment Tool (LCDRAT), the Nord-Trøndelag Health Study (HUNT), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Death (UCLD), the University College London-Incidence (UCLI), the Liverpool Lung Project version 2 (LLP version 2), and the Liverpool Lung Project version 3 (LLP version 3) models. We quantified model calibration as the ratio of expected to observed cases or deaths and discrimination using the area under the receiver operating characteristic curve (AUC). For each model, we also identified risk thresholds that would screen the same number of individuals as each of the US Preventive Services Task Force 2021 (USPSTF-2021), the US Preventive Services Task Force 2013 (USPSTF-2013), and the Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) criteria.Among the participants, 1734 lung cancer cases and 1072 lung cancer deaths occurred within five years of enrolment. Most models had reasonable calibration in most countries, although the LLP version 2 overpredicted risk by more than 50
KW  - Humans
KW  - Lung Neoplasms: diagnosis
KW  - Lung Neoplasms: mortality
KW  - Europe: epidemiology
KW  - Aged
KW  - Male
KW  - Female
KW  - Middle Aged
KW  - Prospective Studies
KW  - Early Detection of Cancer
KW  - Risk Assessment
KW  - Aged, 80 and over
KW  - Incidence
KW  - Risk Factors
LB  - PUB:(DE-HGF)16
C6  - pmid:39179310
DO  - DOI:10.1016/S2589-7500(24)00123-7
UR  - https://inrepo02.dkfz.de/record/292455
ER  -